CN112364145A - Work order processing method and device, electronic equipment and storage medium - Google Patents
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Abstract
The invention discloses a work order processing method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring problem information to be processed, and generating work order data corresponding to the problem information based on a work order generation rule; performing first classification processing on the work order data according to the description information in the work order data, and setting a classification label for the work order data; and identifying the classification labels of the work order data, and distributing the work order data corresponding to each classification label to corresponding processing objects for parallel processing. The work order is accurately distributed and timely processed, and therefore the work order problem processing efficiency is improved.
Description
Technical Field
The embodiment of the invention relates to the technical field of information processing, in particular to a work order processing method and device, electronic equipment and a storage medium.
Background
The work order records and processes the problems, is widely applied to various industries, and faces huge challenges with the rapid increase of the number of feedback problems of users.
Most of the existing work order processing and processing result analysis needs workers to manually process work orders so as to solve the problem of customer feedback. The manual mode is adopted to process the work order, and the problems of poor real-time performance of work order processing and unreasonable work order distribution exist.
Disclosure of Invention
The invention provides a work order processing method and device, electronic equipment and a storage device, which are used for realizing accurate work order distribution and timely processing, thereby improving the work order problem processing efficiency.
In a first aspect, an embodiment of the present invention provides a work order processing method, including:
acquiring problem information to be processed, and generating work order data corresponding to the problem information based on a work order generation rule;
performing first classification processing on the work order data according to the description information in the work order data, and setting a classification label for the work order data;
and identifying the classification labels of the work order data, and distributing the work order data corresponding to each classification label to corresponding processing objects for parallel processing.
In a second aspect, an embodiment of the present invention further provides a work order processing apparatus, where the apparatus includes:
the work order generation module is used for acquiring the problem information to be processed and generating work order data corresponding to the problem information based on a work order generation rule;
the work order classification module is used for performing first classification processing on the work order data according to the description information in the work order data and setting a classification label for the work order data;
and the work order processing module is used for identifying the classification labels of the work order data and distributing the work order data corresponding to each classification label to a corresponding processing object for parallel processing.
In a third aspect, an embodiment of the present invention further provides an electronic device, where the electronic device includes:
one or more processors;
a storage device for storing one or more programs which, when executed by the processor, cause the processor to implement a work order processing method as provided by any embodiment of the invention.
In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the work order processing method provided in any embodiment of the present invention.
According to the technical scheme of the embodiment of the invention, the problem information to be processed is obtained, the work order data corresponding to the problem information is generated based on the work order generation rule, the first classification processing is carried out on the work order data according to the description information in the work order data, the classification label is arranged on the work order data, the work order data corresponding to the problem information is generated through the work order generation rule, so that the work order data is more standard, the unified processing of the problem to be processed is facilitated, the classification processing is carried out on the work order data, the classification label is arranged on the work order data, the modular management of the work order data is facilitated, the work order data corresponding to each classification label is distributed to the corresponding processing object for parallel processing by identifying the classification label of the work order data, the accurate allocation and timely processing of the work order are realized, and the problems of poor real-time performance and unreasonable single allocation in the manual work order data are solved, thereby improving the efficiency of work order problem processing.
Drawings
In order to more clearly illustrate the technical solutions of the exemplary embodiments of the present invention, a brief description is given below of the drawings used in describing the embodiments. It should be clear that the described figures are only views of some of the embodiments of the invention to be described, not all, and that for a person skilled in the art, other figures can be derived from these figures without inventive effort.
Fig. 1 is a schematic flow chart of a work order processing method according to an embodiment of the present invention;
fig. 2 is a schematic flow chart of a work order processing method according to a second embodiment of the present invention;
fig. 3 is a schematic diagram of a work order processing apparatus module according to a third embodiment of the present invention;
fig. 4 is a schematic structural diagram of an electronic device according to a fourth embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention. It should be further noted that, for the convenience of description, only some of the structures related to the present invention are shown in the drawings, not all of the structures.
Example one
Fig. 1 is a schematic flow chart of a work order processing method according to an embodiment of the present invention, where the method is applicable to a case where work order data is classified by setting a classification tag for the work order data, and the method may be executed by a work order processing apparatus, and the work order processing apparatus may be implemented by software and/or hardware, and may be integrated in an electronic device such as a computer or a server.
As shown in fig. 1, the method of the present embodiment includes:
s110, problem information to be processed is obtained, and work order data corresponding to the problem information are generated based on a work order generation rule.
The problem information may be understood as information fed back by the user through the information platform, and the problem information may include, but is not limited to, the following data information: the system comprises a question information identification and a question information content, wherein the question information content comprises a question content, a question description, time information and the like, and the question content can comprise but is not limited to picture information, text information and voice information. The work order generation rule may be a rule corresponding to the preset problem information and the work order, and is used for generating the work order data according to the preset rule by using the problem information.
Specifically, the to-be-processed problem information obtained through the third party platform (i.e., the information platform) is used to generate the work order data according to the work order generation rule, and it should be noted that the manner of obtaining the to-be-processed problem in this embodiment is not limited as long as the to-be-processed problem can be obtained.
In order to improve the validity of the work order data, optionally, after the work order data corresponding to the problem information is generated based on the work order generation rule, the method further includes: and carrying out field integrity verification and logic rule accuracy verification on the work order data, and generating an abnormal identifier in the work order data when verification is abnormal.
The field integrity verification can be understood as verifying whether data corresponding to a field in the work order data is missing. The accuracy verification may be understood as a logic rule for verifying a preset logic relationship in the work order data, where the logic rule may be understood as a rule for setting a logic relationship between fields in the work order data. The integrity exception may be that the field content is null, that is, when it is detected that the field content corresponding to any field in the work order data is null, the work order is abnormal. The accuracy abnormity can be that whether the meditation track link corresponding to the problem type is complete or not is judged according to the problem type of the work order, and when the meditation track link is incomplete, the work order is abnormal. The abnormal mark can be understood as an abnormal label, wherein the abnormal label can be in the form of preset words, characters and the like.
Specifically, when at least one of the conditions that the field in the work order data is empty and the field in the work order data does not accord with the preset logic rule is detected, the work order data is marked as an abnormal work order.
In one embodiment, field integrity verification is performed on the work order data, e.g., a certain work order data includes, a work order number: a; the problem content is as follows: empty; problem description: AAA; time: and (4) X. And carrying out field integrity verification on the work order data.
In another embodiment, the accuracy of the logic rules is verified for the number of work orders, for example, a certain work order data includes the following work order number: b; the problem content is as follows: BB; problem description: BBB; time: x; buddhist channel linking: and (4) X. And verifying the accuracy of the logic rules of the work order data, and marking the work order data as an abnormal work order when incomplete zenith link corresponding to the problem description in the work order data is detected based on the logic relation between the problem description in the preset work order data and the zenith link.
And S120, performing first classification processing on the work order data according to the description information in the work order data, and setting classification labels on the work order data.
The description information of the work order data can be understood as the problem description information corresponding to the problem content of the work order data. The classification can be classified according to category, grade or property, or can classify irregular things into regular things according to different characteristics, so that the things are more regular. In this example, the first classification processing may be understood as classifying the work order data according to the problem description information of the work order data, optionally, extracting a keyword from the problem description information of the work order data, and setting a classification label for the work order data according to a preset correspondence between the keyword and the classification label, where the correspondence between the keyword and the classification label may be one-to-one or many-to-one.
Specifically, based on the generated work order data, the classification labels are set for the work order data according to the corresponding relation between the description information and the classification labels in the work order data, and the advantage of the processing is that the work order modular management is realized. In one embodiment, when the keyword of the description information in the work order data is detected to be "installation", the classification label of the work order data is set as the classification label 1 according to the one-to-one correspondence between the preset keyword "installation" and the classification label 1.
In another embodiment, when it is detected that the keywords of the description information in the work order data at least include "device", "need", and the like, the classification label of the work order data is set as the classification label 2 according to the preset keyword "device" and the many-to-one correspondence between the "need" and the classification label 2, so that the processing method has the advantages of further classifying the work order data of the need type, facilitating the processing of the work order data, and improving the processing efficiency of the work order data.
And S130, identifying the classification labels of the work order data, and distributing the work order data corresponding to each classification label to corresponding processing objects for parallel processing.
The processing object may be a person in charge of the service line or an electronic device performing processing. Parallel processing may be understood as synchronous processing of work order data of different classifications based on classification tags.
Specifically, classification tags set based on the work order data identify the classification tags of the work order data, and distribute the work order data corresponding to the classification tags to processing objects corresponding to the classification tags, so that a business line responsible person can process the work order data in real time, for example, the classification tags 1 are distributed to the business line responsible person corresponding to the classification tags 1, and the classification tags 2 are distributed to the processing objects corresponding to the classification tags 2, so that the business responsible person can process the work order data in time, it is required to say that the classification tags 1 and the classification tags 2 are two types of classification tags of the work order data, the processing objects corresponding to the work order data corresponding to different classification tags are different, that is, the business line responsible persons processed correspondingly to different classification tags are different.
In order to improve the efficiency of processing the work order data, it is preferable that before distributing the work order data corresponding to each classification label to the corresponding processing object for parallel processing, the method further includes:
and performing secondary integrity verification on the work order data based on the classification label of the work order data.
The secondary integrity verification can be understood as whether the data corresponding to the label information of the work order data is empty or not.
Optionally, before the work order number corresponding to the classification tag is distributed to the corresponding object for parallel processing, whether the data corresponding to the tag information in the work order data is empty is judged according to the classification tag of the work order data, so that the advantage of monitoring the work order data in real time is provided, which is beneficial to problem closed-loop management of the work order data and guarantees the integrity and effectiveness of the work order data.
According to the technical scheme of the embodiment of the invention, the problem information to be processed is obtained, the work order data corresponding to the problem information is generated based on the work order generation rule, and the problem that the problem information fed back by a user is irregular is solved. The method comprises the steps of carrying out first classification processing on work order data according to description information in the work order data, setting classification labels on the work order data, generating work order data corresponding to problem information through a work order generation rule so as to enable the work order data to be more standard, facilitating unified processing of problems to be processed, carrying out classification processing on the work order data, setting classification labels on the work order data so as to facilitate modular management of the work order data, distributing the work order data corresponding to the classification labels to corresponding processing objects for parallel processing by identifying the classification labels of the work order data, achieving accurate work order distribution and timely processing, solving the problems of poor real-time performance and unreasonable single distribution of manually processed work order data, and improving the efficiency of work order problem processing.
On the basis of the above embodiment, optionally, data statistics is performed on the work order data according to at least one item of the total number of the work order data, the classification label of each work order data, and the completion state of each work order data, so as to form a work order data report.
The completion status of the work order data may include unprocessed, pending, in-process, out-of-date, and completed status.
Specifically, based on the work order data, comprehensive statistics can be performed on the work order processing according to the total quantity of the work order data, the classification labels of the work order data and the completion state of the work order data to form a work order data report, so that the work order proportion trend, the work order proportion analysis, the common problem optimization, the excess work order summarization, the work order completion rate analysis and the like can be performed on the analysis of the work order trend of the output service, real-time data analysis report query is realized, batch problems are promoted to be commercialized, operated and instrumentized, the time required by data statistics and output report is shortened, and the effects of saving energy and improving efficiency are achieved.
On the basis of the embodiment, in order to feed back the work order data to the user in time and determine the priority of the work order data, optionally, the detailed information of the user is obtained and synchronized in real time, the users are grouped according to the user authority, and the user authority group information is displayed.
Example two
Fig. 2 is a schematic flow chart of a work order processing method according to a second embodiment of the present invention, and details a work order data processing method based on the second embodiment.
The technical terms that are the same as or corresponding to the above embodiments are not repeated herein.
As shown in fig. 2, the method of the present embodiment includes:
s210, obtaining problem information to be processed, identifying field content in the problem information, calling a visual work order template, and adding the identified field content to a corresponding position of the visual work order template to form visual work order data.
The visualization is to convert data into graphics or images to be displayed on a screen by using computer graphics and image processing technology, and perform interactive processing. In this embodiment, the visualization template may be understood as a visualization interface, and the visualization template is a preset work order template interface and is used for forming a visualization work order based on field contents of problem information of the work order data. The formed work order data can be displayed on a display interface, so that operators can visually acquire information on the visual work order.
The present embodiment does not limit the technology for identifying the field content in the problem information, and may be implemented as long as the field content in the problem information can be identified.
Specifically, the problem information to be processed is obtained, a visual work order template preset in advance is called by identifying the field content of the problem information to be processed, the identified field content is added to the position corresponding to the visual work order template, and visual work order data are formed, so that the problem information to be processed forms standard work order data, and the subsequent problem information can be conveniently processed and counted. Illustratively, problem information to be processed is acquired, corresponding contents of the problem content, the problem description, time and other fields of the problem information are acquired by identifying the corresponding fields of the problem content, the problem description, the time and the like in the problem information, and the contents corresponding to the problem information fields are added to corresponding interface element positions in a visualization template respectively according to the corresponding relationship between the interface elements and the field contents in the visualization template, for example, the field problem description fields in the problem information of the problem to be processed correspond to the interface elements of the problem description in the visualization template, so as to form a visualization work order.
And S220, performing first classification processing on the work order data according to the description information in the work order data, and setting classification labels on the work order data.
The classification label is a label type preset in advance according to experience, wherein the classification label at least comprises an FAQ problem, a demand problem and a BUG problem.
In order to improve the processing efficiency of the work order data, in an embodiment, optionally, the performing a first classification process on the work order data according to the description information in the work order data includes: identifying keywords in the description information, matching the keywords in a preset keyword set corresponding to each classification, and determining a first classification result according to a matching result;
specifically, in order to classify the work order data quickly and efficiently, optionally, the keywords are identified from the description information in the work order data, and the keywords are matched with the preset keyword set in each classification, so that the classification result of the keywords is determined according to the matching result.
Illustratively, the set of keywords in category 1 includes keyword 1, keyword 2, keyword 3, etc., and the set of keywords in category 2 includes keyword 4, keyword 5, and keyword 6. And when detecting that the keywords in the description information in the work order data are matched with the keywords 4, determining the work order data as the classification 2. And if the optional keywords in the description information in the detection order data are matched with the keywords 2 and the keywords 3, determining the classification 1 of the work order data. In order to improve the efficiency of splitting processing of the work order data, in another embodiment, optionally, the performing, according to the description information in the work order data, the first classification processing on the work order data further includes: and inputting the description information into a pre-trained semantic classification model, and determining a first classification result based on an output result of the semantic classification model.
The semantic classification model is used for classifying the problem description information in the work order data.
Specifically, description information in the historical work order data and classification labels corresponding to the description information in the historical work order data are obtained, and training sample data are generated according to the description information of the historical work order data and the classification labels corresponding to the description information. And taking the description information of the historical work order data of the training sample data as the input of the original semantic classification model to obtain an output problem description information classification label corresponding to the training sample data. And obtaining a semantic classification model based on the output problem description information classification label and the classification label corresponding to the description information. And inputting the description information in the work order data into a semantic classification model obtained by training to obtain a classification result corresponding to the description information in the work order data, thereby determining the classification of the work order data.
It should be noted that the semantic training model in this embodiment is not limited, as long as the problem description information of the work order data can be classified.
And S230, when the classification label of the work order data is an FAQ problem, identifying the problem content of the work order data, determining a processing mode corresponding to the work order data, updating the processing mode into the work order data, and distributing the updated work order data to a first processing object.
The problem content in the work order data with the classification label of the FAQ problem may include related problem content of system normal operation and product design specification, and the processing mode of the work order data with the classification label of the FAQ problem may be that the user is guided to independently solve through the FAQ operation, where the FAQ operation may be online editing, online deletion, or attachment uploading (picture, WORD, video, etc.). The first processing object may be understood as a user or a third party platform that handles the type of FAQ issue, wherein the first processing object may be one or more.
Specifically, based on the classification label for identifying the work order data, when the classification label for detecting the work order data is an FAQ problem, the problem content of the work order data is identified, and the processing mode of the work order data is determined according to the identified problem content in the work order data.
And S240, when the classification label of the work order data is a demand problem, identifying the demand type of the work order data, updating the demand type into the work order data, and distributing the updated work order data to a second processing object.
The requirement types include but are not limited to business requirements, functional requirements and user requirements, wherein the user requirements do not include user personalized requirements. The second processing object may be understood as processing order data for the demand issue type.
Specifically, based on the classification label of discernment work order data, when the classification label that detects work order data is the demand problem, based on the problem description information of work order data, set up the demand secondary classification label of work order data, wherein, demand secondary classification label can include following several kinds of types: the business requirement label, the function requirement label and the user requirement label update the requirement type label to the work order data by identifying the specific requirement type corresponding to the requirement secondary classification label of the work order data, and distribute the updated work order data to a plurality of devices, so that the responsible person of the related business line can timely process the requirement problem in the related work order data.
In this embodiment, optionally, the identification of the demand type of the work order data may establish a corresponding relationship with a keyword in the problem content of the work order data by presetting the demand classification tag, and the demand type of the work order data is determined by detecting the keyword in the problem content of the work order data. Optionally, the requirement type of the work order data may be identified by determining the requirement type of the work order data in a mechanical manner. In this embodiment, the manner of identifying the requirement type of the work order data is not limited as long as the requirement type of the work order data can be identified.
On this basis, in order to know the workload and the demand conversion rate of each service in time, optionally, a demand analysis report is formed by presetting demand indexes, so that the advantage of processing is that the newly added demand condition in the time period is analyzed in real time and the workload is convenient to count.
And S250, when the classification label of the work order data is a BUG problem, identifying the BUG type of the work order data, updating the BUG type into the work order data, and distributing the updated work order data to a third processing object.
Among them, the BUG types may include, but are not limited to, the following types: the method comprises the steps of functional BUG, interface BUG, compatible BUG and blocking on-line flow. The third processing object may be understood to process work order data of the BUG issue type.
Specifically, based on the classification label for identifying the work order data, when the classification label for the work order data is detected to be a BUG problem, based on the problem description information of the work order data,
setting BUG secondary classification labels of work order data, wherein the BUG secondary classification labels can comprise the following types: the method comprises the steps of functional BUG, interface BUG, compatible BUG and blocking on-line flow, wherein a BUG type label is updated to work order data by identifying a specific BUG type corresponding to a BUG secondary classification label of the work order data, and the updated work order data is distributed to a plurality of devices, so that a related business line responsible person can timely process BUG problems in the related work order data.
In this embodiment, optionally, the identification of the BUG type of the work order data may establish a corresponding relationship with a keyword in the problem content of the work order data by preset BUG classification tags, and determine the BUG type of the work order data by detecting the keyword in the problem content of the work order data. Optionally, identifying the BUG type of the work order data may also be determining the BUG type of the work order data in a mechanical manner. In this embodiment, the method for identifying the BUG type of the work order data is not limited as long as the BUG type of the work order data can be identified.
On the basis, in order to process the work order quantity of the BUG problem type in time, optionally, a BUG analysis report is formed by presetting a BUG index, and the processing has the advantages that the newly increased BUG problem condition in the time period is analyzed in real time, and the work order quantity is conveniently counted.
It should be noted that, there is no precedence order among steps S230, S240, and S250, and the steps may be executed sequentially or synchronously.
According to the technical scheme of the embodiment of the invention, the problem information to be processed is obtained, the work order data corresponding to the problem information is generated based on the work order generation rule, the first classification processing is carried out on the work order data according to the description information in the work order data, the classification label is arranged on the work order data, the work order data corresponding to the problem information is generated through the work order generation rule, so that the work order data is more standard, the unified processing of the problem to be processed is facilitated, the classification processing is carried out on the work order data, the classification label is arranged on the work order data, the modular management of the work order data is facilitated, the work order data corresponding to each classification label is distributed to the corresponding processing object for parallel processing by identifying the classification label of the work order data, the accurate allocation and timely processing of the work order are realized, and the problems of poor real-time performance and unreasonable single allocation in the manual work order data are solved, thereby improving the efficiency of work order problem processing.
EXAMPLE III
Fig. 3 is a schematic diagram of a work order processing apparatus module according to a third embodiment of the present invention, in which the work order processing apparatus includes: a work order generation module 310, a work order classification module 320, and a work order processing module 330.
The work order generation module 310 is configured to obtain problem information to be processed, and generate work order data corresponding to the problem information based on a work order generation rule; the work order classification module 320 is configured to perform first classification processing on the work order data according to description information in the work order data, and set a classification label for the work order data; the work order processing module 330 is configured to identify the classification tags of the work order data, and distribute the work order data corresponding to each classification tag to corresponding processing objects for parallel processing.
According to the technical scheme of the embodiment of the invention, the problem information to be processed is obtained through a work order generating module, the work order data corresponding to the problem information is generated based on a work order generating rule, the work order data is subjected to first classification processing according to the description information in the work order data through a work order classifying module, the work order data is provided with a classifying label, the work order data corresponding to the problem information is generated through the work order generating rule, so that the work order data is more standard, the uniform processing of the problems to be processed is facilitated, the work order data is classified and processed, the classifying label is provided for the work order data, the work order data modularization management is facilitated, the classifying label of the work order data is identified through the work order processing module, the work order data corresponding to each classifying label is distributed to the corresponding processing object for parallel processing, and the accurate distribution and timely processing of the work order are realized, the problems of poor real-time performance and unreasonable single distribution in manual work order data processing are solved, and therefore work order problem processing efficiency is improved.
Optionally, the work order generating module 310 is configured to identify field content in the problem information, call a visual work order template, add the identified field content to a corresponding position of the visual work order template, and form visual work order data.
Optionally, the classification tag includes: FAQ issues, demand issues, and BUG issues;
the work order processing module 330 is configured to, when the classification label of the work order data is an FAQ problem, identify the problem content of the work order data, determine a processing manner corresponding to the work order data, update the processing manner to the work order data, and distribute the updated work order data to a first processing object;
when the classification label of the work order data is a demand problem, identifying a demand type of the work order data, updating the demand type into the work order data, and distributing the updated work order data to a second processing object;
and when the classification label of the work order data is a BUG problem, identifying the BUG type of the work order data, updating the BUG type into the work order data, and distributing the updated work order data to a third processing object.
Optionally, the work order classification module 320 is configured to identify a keyword in the description information, match the keyword in a preset keyword set corresponding to each classification, and determine a first classification result according to a matching result;
or inputting the description information into a pre-trained semantic classification model, and determining a first classification result based on an output result of the semantic classification model.
Optionally, the apparatus further comprises: the work order verification module 340 is configured to perform field integrity verification and accuracy verification of a logic rule on the work order data after the work order data corresponding to the problem information is generated based on a work order generation rule, and generate an abnormal identifier in the work order data when verification is abnormal.
Optionally, the work order verification module 340 is further configured to perform secondary integrity verification on the work order data based on the classification tags of the work order data before distributing the work order data corresponding to each classification tag to a corresponding processing object for parallel processing.
Optionally, the work order statistics module 350 is further configured to perform data statistics on the work order data according to at least one item of the total number of the work order data, the classification label of each work order data, and the completion state of each work order data, so as to form a work order data report.
The device can execute the work order processing method provided by any embodiment of the invention, and has the corresponding functional modules and beneficial effects of executing the work order processing method.
Example four
Fig. 4 is a schematic structural diagram of an electronic device according to a fourth embodiment of the present invention. FIG. 4 illustrates a block diagram of an exemplary device 40 suitable for use in implementing embodiments of the present invention. The device 40 shown in fig. 4 is only an example and should not bring any limitation to the function and scope of use of the embodiments of the present invention.
As shown in FIG. 4, device 40 is embodied in a general purpose computing device. The components of device 40 may include, but are not limited to: one or more processors or processing units 401, a system memory 402, and a bus 403 that couples the various system components (including the system memory 402 and the processing unit 401).
The system memory 402 may include computer system readable media in the form of volatile memory, such as Random Access Memory (RAM)404 and/or cache memory 405. Device 40 may further include other removable/non-removable, volatile/nonvolatile computer system storage media. By way of example only, storage system 406 may be used to read from and write to non-removable, nonvolatile magnetic media (not shown in FIG. 4, and commonly referred to as a "hard drive"). Although not shown in FIG. 4, a magnetic disk drive for reading from and writing to a removable, nonvolatile magnetic disk (e.g., a "floppy disk") and an optical disk drive for reading from or writing to a removable, nonvolatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to the bus 403 by one or more data media interfaces. Memory 402 may include at least one program product having a set (e.g., at least one) of program modules that are configured to carry out the functions of embodiments of the invention.
A program/utility 408 having a set (at least one) of program modules 407 may be stored, for example, in memory 402, such program modules 407 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each of which examples or some combination thereof may comprise an implementation of a network environment. Program modules 407 generally perform the functions and/or methods of the described embodiments of the invention.
The processing unit 401 executes various functional applications and data processing by running a program stored in the system memory 402, for example, to implement the work order processing method provided by the embodiment of the present invention.
EXAMPLE five
Fifth, an embodiment of the present invention further provides a storage medium containing computer-executable instructions, which when executed by a computer processor, are configured to perform a method for processing a work order.
The method comprises the following steps:
acquiring problem information to be processed, and generating work order data corresponding to the problem information based on a work order generation rule;
performing first classification processing on the work order data according to the description information in the work order data, and setting a classification label for the work order data;
and identifying the classification labels of the work order data, and distributing the work order data corresponding to each classification label to corresponding processing objects for parallel processing.
Computer storage media for embodiments of the invention may employ any combination of one or more computer-readable media. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations for embodiments of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in greater detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.
Claims (10)
1. A work order processing method is characterized by comprising the following steps:
acquiring problem information to be processed, and generating work order data corresponding to the problem information based on a work order generation rule;
performing first classification processing on the work order data according to the description information in the work order data, and setting a classification label for the work order data;
and identifying the classification labels of the work order data, and distributing the work order data corresponding to each classification label to corresponding processing objects for parallel processing.
2. The method according to claim 1, wherein the generating work order data corresponding to the problem information based on the work order generation rule comprises:
and identifying field content in the problem information, calling a visual work order template, and adding the identified field content to the corresponding position of the visual work order template to form visual work order data.
3. The method of claim 1, wherein the classification tag comprises: FAQ issues, demand issues, and BUG issues;
the identifying the classification labels of the work order data, distributing the work order data corresponding to each classification label to a corresponding processing object for parallel processing, includes:
when the classification label of the work order data is an FAQ problem, identifying the problem content of the work order data, determining a processing mode corresponding to the work order data, updating the processing mode into the work order data, and distributing the updated work order data to a first processing object;
when the classification label of the work order data is a demand problem, identifying a demand type of the work order data, updating the demand type into the work order data, and distributing the updated work order data to a second processing object;
and when the classification label of the work order data is a BUG problem, identifying the BUG type of the work order data, updating the BUG type into the work order data, and distributing the updated work order data to a third processing object.
4. The method of claim 1, wherein the performing a first classification process on the work order data according to the description information in the work order data comprises:
identifying keywords in the description information, matching the keywords in a preset keyword set corresponding to each classification, and determining a first classification result according to a matching result;
or inputting the description information into a pre-trained semantic classification model, and determining a first classification result based on an output result of the semantic classification model.
5. The method of claim 1, wherein after generating the work order data corresponding to the problem information based on a work order generation rule, further comprising:
and carrying out field integrity verification and logic rule accuracy verification on the work order data, and generating an abnormal identifier in the work order data when verification is abnormal.
6. The method of claim 1, wherein prior to distributing the work order data corresponding to each category label to the corresponding processing object for parallel processing, the method further comprises:
and performing secondary integrity verification on the work order data based on the classification label of the work order data.
7. The method of claim 1, further comprising:
and performing data statistics on the work order data according to at least one item of the total number of the work order data, the classification label of each work order data and the completion state of each work order data to form a work order data report.
8. A work order processing apparatus, comprising:
the work order generation module is used for acquiring the problem information to be processed and generating work order data corresponding to the problem information based on a work order generation rule;
the work order classification module is used for performing first classification processing on the original work order according to the description information in the work order data and setting a classification label for the work order data;
and the work order processing module is used for identifying the classification labels of the work order data and distributing the work order data corresponding to each classification label to a corresponding processing object for parallel processing.
9. An electronic device, characterized in that the electronic device comprises:
one or more processors;
storage means for storing one or more programs which, when executed by the processor, cause the processor to carry out a method of work order processing as claimed in any one of claims 1 to 7.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out a method of work order processing according to any one of claims 1-7.
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